{"id":"W4405797009","doi":"10.1158/2767-9764.crc-24-0287","title":"Clinical Proteomics Reveals Vulnerabilities in Noninvasive Breast Ductal Carcinoma and Drives Personalized Treatment Strategies","year":2024,"lang":"en","type":"article","venue":"Cancer Research Communications","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Winnipeg; University of Manitoba; IGNIS Innovation (Canada); Jewish General Hospital; Research Institute in Oncology and Hematology; McGill University; CancerCare Manitoba","funders":"National Cancer Institute; Warren Y. Soper Charitable Trust; Fondation De Famille Alvin Segal; Jewish General Hospital; Fondation du cancer du sein du Québec; Genome Canada; Faculty of Medicine, McGill University; McGill University","keywords":"Druggability; Proteomics; Breast cancer; Ductal carcinoma; PI3K/AKT/mTOR pathway; Biology; Quantitative proteomics; Cancer; Bioinformatics; Cancer research; Medicine; Computational biology; Oncology; Pathology; Internal medicine; Gene; Signal transduction; Genetics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006043062,0.0001602454,0.0002433042,0.0001317194,0.000386654,0.0002187527,0.0006120176,0.000125036,0.0001831824],"category_scores_gemma":[0.00007042358,0.0001466934,0.00008386105,0.0003178952,0.00138682,0.0002345073,0.0003901075,0.0008356748,0.000007704354],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005436732,"about_ca_system_score_gemma":0.000744226,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00127296,"about_ca_topic_score_gemma":0.001003365,"domain_scores_codex":[0.9984229,0.0002249738,0.0003984066,0.0004298993,0.0001850569,0.0003387693],"domain_scores_gemma":[0.9974882,0.0009114018,0.00004709497,0.001237542,0.0001934981,0.0001222668],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0001952479,0.0008877129,0.07975078,0.0008997502,0.0002503819,0.00004801141,0.01214653,0.00004397197,0.1901915,0.6740063,0.0007931407,0.04078675],"study_design_scores_gemma":[0.005879496,0.0009380072,0.02336754,0.004911215,0.0002325436,0.0006617399,0.07385136,0.01975837,0.0717783,0.6048153,0.1909377,0.002868443],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9700056,0.01447328,0.0004794961,0.00693809,0.00001870576,0.0009294141,0.0006417054,0.0001669019,0.006346792],"genre_scores_gemma":[0.9533595,0.02254337,0.01675003,0.00001228352,0.0001064371,0.005541406,0.00009231672,0.000034162,0.001560503],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1901445,"threshold_uncertainty_score":0.5981982,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1277857034909281,"score_gpt":0.4749458926351294,"score_spread":0.3471601891442013,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}